Wind and Structures

  • 제34권6호
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  • Pages.469-482
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  • 2022
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  • 1226-6116(pISSN)
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  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Estimating quantiles of extreme wind speed using generalized extreme value distribution fitted based on the order statistics

  • Liu, Y.X. (Department of Civil and Environmental Engineering, University of Western Ontario) ;
  • Hong, H.P. (Department of Civil and Environmental Engineering, University of Western Ontario)
  • 투고 : 2021.09.26
  • 심사 : 2022.03.17
  • 발행 : 2022.06.25
⟨ 이전 논문 다음 논문 ⟩

초록

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

키워드

과제정보

The financial support received from the Natural Sciences and Engineering Research Council of Canada (RGPIN-2016-04814, for HPH) is acknowledged.

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